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Brooksource · 1 week ago

Machine Learning Consultant

United States

Part-time

Remote

Senior Level

$75/hr - $80/hr

Brooksource is seeking an experienced Azure Cloud Specialist with strong expertise in Machine Learning, Data Engineering, and Recommendation Systems. The role involves supporting and extending data and ML infrastructure, owning end-to-end pipelines in Azure, and delivering high-quality recommender models for outcomes-focused applications.

EmploymentHuman ResourcesInformation Technology

Growth Opportunities

H1B Sponsor Likely

Responsibilities

Design, train, and tune recommendation models: collaborative filtering, content-based, and hybrid approaches

Implement and compare LightFM loss functions (WARP, BPR, logistic) and optimize for implicit vs. explicit feedback scenarios

Engineer features for user/item interactions, incorporate side features (user/item metadata), and address cold-start challenges

Build, optimize, and troubleshoot ETL/ELT pipelines using Azure Data Factory, Databricks (Spark), and Azure Storage services

Implement robust data preprocessing pipelines; manage train/test splits tailored to recommender data (e.g., time-based, leave-one-out)

Handle sparse matrices efficiently (e.g., using numpy, scipy) and scalable data flows for large interaction datasets

Establish hyperparameter tuning workflows (learning rate, epochs, regularization) and model versioning practices

Coordinate Azure resources and integrations across multiple systems for seamless data and model deployment (APIs, batch/stream)

Define and track evaluation metrics—precision@k, recall@k, AUC, coverage/diversity—through experiments and dashboards

Monitor model performance post-deployment; detect drift and trigger retraining when needed

Document technical decisions, configurations, pipelines, and model cards for transparency and reproducibility

Qualification

Azure CloudMachine LearningRecommendation SystemsData EngineeringPythonCollaboration

Required

Strong Python fundamentals with numpy, pandas, scipy; familiarity with latent factor models, vector operations, dot products, and basic optimization

Hands‑on experience building recommender systems (collaborative/content‑based/hybrid) and working knowledge of LightFM (implicit/explicit feedback, WARP/BPR/logistic losses)

Practical experience in feature engineering, cold‑start handling, and sparse matrix workflows

Proven ability to develop and deploy ML models to production in Azure; strong pipeline skills with Data Factory, Databricks/Spark, and Azure Storage

Experience with train/test splitting for recommender data, hyperparameter tuning, and model versioning

Ability to work independently with minimal supervision in asynchronous environments; excellent communication skills

Preferred

Experience with MLOps tooling and best practices (CI/CD for ML, model registry, experiment tracking)

Familiarity with API integration patterns (e.g., MuleSoft or similar) for serving recommendations

Prior work in education, workforce, or outcomes‑focused public sector systems

Company

Brooksource

Glassdoor4.0

Brooksource is a single source for project and supplemental support through contract employment, contract-to-hire labor employment.

Founded in 2000

Indianapolis, Indiana, USA

1001-5000 employees

http://www.brooksource.com

H1B Sponsorship

Brooksource has a track record of offering H1B sponsorships. Please note that this does not guarantee sponsorship for this specific role. Below presents additional info for your reference. (Data Powered by US Department of Labor)

Distribution of Different Job Fields Receiving Sponsorship

Represents job field similar to this job

Trends of Total Sponsorships

2020 (10)